Towards Object Recognition using HDR Video, Stereoscopic Depth Information and SIFT
Abstract
In this paper we propose a framework that will recognise objects from a moving platform using scale invariant features, high dynamic range (HDR) video and stereoscopic depth information. The paper focuses on initial work involving feature extraction from HDR images using SIFT. Initial results show an increase in the number of features extracted from HDR images compared to conventional, low dynamic range (LDR), images.
BibTeX
@inproceedings {10.2312:LocalChapterEvents:TPCG:TPCG09:165-168,
booktitle = {Theory and Practice of Computer Graphics},
editor = {Wen Tang and John Collomosse},
title = {{Towards Object Recognition using HDR Video, Stereoscopic Depth Information and SIFT}},
author = {May, Michael and Morris, Tim and Markham, Keith and Crowther, William J. and Turner, Martin J.},
year = {2009},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-71-5},
DOI = {10.2312/LocalChapterEvents/TPCG/TPCG09/165-168}
}
booktitle = {Theory and Practice of Computer Graphics},
editor = {Wen Tang and John Collomosse},
title = {{Towards Object Recognition using HDR Video, Stereoscopic Depth Information and SIFT}},
author = {May, Michael and Morris, Tim and Markham, Keith and Crowther, William J. and Turner, Martin J.},
year = {2009},
publisher = {The Eurographics Association},
ISBN = {978-3-905673-71-5},
DOI = {10.2312/LocalChapterEvents/TPCG/TPCG09/165-168}
}